منابع مشابه
Answer Retrieval From Extracted Tables
Question answering (QA) on table data, which contains densely packed information in two-dimensional form, is a challenging information retrieval task. Data can be placed at a distance from the metadata describing it. The metadata itself can be difficult to identify given the layout of a particular table. This paper describes a QA system for tables created with both machine learning and heuristi...
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Question classification is an important task with wide applications. However, traditional techniques treat questions as general sentences, ignoring the corresponding answer data. In order to consider answer information into question modeling, we first introduce novel group sparse autoencoders which refine question representation by utilizing group information in the answer set. We then propose ...
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Classifying question sentences into their corresponding categories is an important task with wide applications, for example in many websites’ FAQ sections. However, traditional question classification techniques do not fully utilize the wellprepared answer data which has great potential for improving question representation and could lead to better classification performance. In order to encode...
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Multiple choice questions (MCQs) are a common data gathering tool. We extend the Latent Dirichlet Allocation (LDA) framework to a collection of MCQ surveys. Topic discovery is turned into group discovery based on survey response patterns. Question choices are equivalent to vocabulary words and are conditioned on the question and the latent group that is used to cluster the survey responders. Th...
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Mining online discussions to extract answers is an important research problem. Methods proposed in the past used supervised classifiers trained on labeled data. But, collecting training data for each target forum is labor intensive and time consuming, thus limiting their deployment. A recent approach had proposed to extract answers in an unsupervised manner, by taking cues from their repetition...
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ژورنال
عنوان ژورنال: FEBS Letters
سال: 1995
ISSN: 0014-5793
DOI: 10.1016/0014-5793(56)90003-5